Special issue: Development of service-based and agent-based computing systems

This special issue presents the best papers from theworkshops onService-OrientedComputing: Agents, Semantics and Engineering (SOCASE 2010) held in May 2010 in Toronto, Canada and the IEEE 2010 First International Workshop on Service-Oriented Computing and Multi-Agent Systems (SOCMAS 2010) held in July 2010 in Miami, Florida, USA. The goal of the workshops was to present the recent significant developments at the intersections of multi-agent systems, semantic technology, and service-oriented computing, and to promote crossfertilization of techniques. In particular, the workshops attempted to identify techniques from research on multi-agent systems and semantic technology that will have the greatest impact on automating serviceoriented application construction and management, focusing on critical challenges such as service quality assurance, reliability, and adaptability. The areas of service-oriented computing and Semantic Web services offer much of real interest to the multi-agent system community, including similarities in system architectures and provision processes, powerful tools, and the focus on many related issues including quality of service, security, and reliability. In addition, service-oriented computing and Semantic Web services offer various diverse application fields for both the concepts and methodologies of intelligent agent and multi-agent systems. Similarly, techniques developed in the multi-agent systems research community promise to have a strong impact on this fast growing technology. In particular, they enable services to be discovered and enacted across enterprise boundaries. If an organisation bases its success on services provided by others, then it must be able to trust that the services will perform as promised, whenever needed. Researchers in multi-agent systems have investigated such trust mechanisms

Method integration: An approach to develop agent oriented methodologies

Agent oriented software engineering (AOSE) is an emerging field in computer science  and  proposes some systematic ideas for multi agent systems analysis, implementation and maintenance. Despite the various methodologies introduced in the agent-oriented software engineering, the main challenges are defects in different aspects of methodologies. According to the defects resulted from weaknesses in agent oriented methodologies in different aspects, a combinatory solution named ARA using, ASPECS, ROADMAP and AOR has been proposed. The three methodologies were analyzed in a comprehensive analytical framework according to concepts and Perceptions, modeling language, process and pragmatism. According to time and resource limitations, sample methodologies for evaluation and in titration were selected. This selection was based on the use of methodologies' and their combination ability. The evaluation show that, the ROADMAP methodology supports stages of agent-oriented systems' analysis and the design stage is not complete because it doesn’t model all semi agents. On the other hand, since AOR and ASPECS methodologies support the design stage and inter agent interactions, a mixed methodology has been proposed and is a combination of analysis stage of ROADMAP methodology and design stage of AOR and ASPECS methodologies. Furthermore, to increase the performance of proposed methodology of actor models, service model, capability and programming were also added to this proposed methodology. To describe its difference phases, it was used in a case study too. Results of this project can pave the way to introduce future agent-oriented methodologies

Agent-based hybrid framework for decision making on complex problems

Electronic commerce and the Internet have created demand for automated systems that can make complex decisions utilizing information from multiple sources. Because the information is uncertain, dynamic, distributed, and heterogeneous in nature, these systems require a great diversity of intelligent techniques including expert systems, fuzzy logic, neural networks, and genetic algorithms. However, in complex decision making, many different components or sub-tasks are involved, each of which requires different types of processing. Thus multiple such techniques are required resulting in systems called hybrid intelligent systems. That is, hybrid solutions are crucial for complex problem solving and decision making. There is a growing demand for these systems in many areas including financial investment planning, engineering design, medical diagnosis, and cognitive simulation. However, the design and development of these systems is difficult because they have a large number of parts or components that have many interactions. From a multi-agent perspective, agents in multi-agent systems (MAS) are autonomous and can engage in flexible, high-level interactions. MASs are good at complex, dynamic interactions. Thus a multi-agent perspective is suitable for modeling, design, and construction of hybrid intelligent systems. The aim of this thesis is to develop an agent-based framework for constructing hybrid intelligent systems which are mainly used for complex problem solving and decision making. Existing software development techniques (typically, object-oriented) are inadequate for modeling agent-based hybrid intelligent systems. There is a fundamental mismatch between the concepts used by object-oriented developers and the agent-oriented view. Although there are some agent-oriented methodologies such as the Gaia methodology, there is still no specifically tailored methodology available for analyzing and designing agent-based hybrid intelligent systems. To this end, a methodology is proposed, which is specifically tailored to the analysis and design of agent-based hybrid intelligent systems. The methodology consists of six models - role model, interaction model, agent model, skill model, knowledge model, and organizational model. This methodology differs from other agent-oriented methodologies in its skill and knowledge models. As good decisions and problem solutions are mainly based on adequate information, rich knowledge, and appropriate skills to use knowledge and information, these two models are of paramount importance in modeling complex problem solving and decision making. Follow the methodology, an agent-based framework for hybrid intelligent system construction used in complex problem solving and decision making was developed. The framework has several crucial characteristics that differentiate this research from others. Four important issues relating to the framework are also investigated. These cover the building of an ontology for financial investment, matchmaking in middle agents, reasoning in problem solving and decision making, and decision aggregation in MASs. The thesis demonstrates how to build a domain-specific ontology and how to access it in a MAS by building a financial ontology. It is argued that the practical performance of service provider agents has a significant impact on the matchmaking outcomes of middle agents. It is proposed to consider service provider agents\u27 track records in matchmaking. A way to provide initial values for the track records of service provider agents is also suggested. The concept of ‘reasoning with multimedia information’ is introduced, and reasoning with still image information using symbolic projection theory is proposed. How to choose suitable aggregation operations is demonstrated through financial investment application and three approaches are proposed - the stationary agent approach, the token-passing approach, and the mobile agent approach to implementing decision aggregation in MASs. Based on the framework, a prototype was built and applied to financial investment planning. This prototype consists of one serving agent, one interface agent, one decision aggregation agent, one planning agent, four decision making agents, and five service provider agents. Experiments were conducted on the prototype. The experimental results show the framework is flexible, robust, and fully workable. All agents derived from the methodology exhibit their behaviors correctly as specified

A survey of agent-oriented methodologies

This article introduces the current agent-oriented methodologies. It discusses what approaches have been followed (mainly extending existing object oriented and knowledge engineering methodologies), the suitability of these approaches for agent modelling, and some conclusions drawn from the survey

Engineering of service-oriented automation systems: a survey

The evolution of manufacturing systems and the emergence of decentralised control require flexibility at various levels of their lifecycle. New emerging methods, such as multi-agent and service-oriented systems are major research topics in the sense of revitalizing the traditional production procedures. This paper takes an overview of the serviceoriented approach in terms of platform and engineering tools, from the perspective of automation and production systems. From the basic foundation to the more complex interactions, service-oriented architectures and its implementation in form of web services provide diverse and quality proved features that are welcome to different states of the production systems’ life-cycle. Key elements are the concepts of modelling and collaboration, which enhance the automatic binding and synchronisation of individual low-value services to more complex and meaningful structures. Such interactions can be specified by Petri nets, a mathematically well founded tool with features that enhance towards the modelling of systems. The right application of different methodologies together should motivate the development of service-oriented manufacturing systems that embrace the vision of collaborative automation.The authors would like to thank the European Commission and the partners of Network of Excellence “Innovative Production Machines and Systems” (http://www.iproms.org/) and the SOCRADES project (http://www.socrades.eu) for their support.info:eu-repo/semantics/publishedVersio

Engineering of service-oriented automation systems: a survey

The evolution of manufacturing systems and the emergence of decentralised control require flexibility at various levels of their lifecycle. New emerging methods, such as multi-agent and service-oriented systems are major research topics in the sense of revitalizing the traditional production procedures. This paper takes an overview of the serviceoriented approach in terms of platform and engineering tools, from the perspective of automation and production systems. From the basic foundation to the more complex interactions, service-oriented architectures and its implementation in form of web services provide diverse and quality proved features that are welcome to different states of the production systems’ life-cycle. Key elements are the concepts of modelling and collaboration, which enhance the automatic binding and synchronisation of individual low-value services to more complex and meaningful structures. Such interactions can be specified by Petri nets, a mathematically well founded tool with features that enhance towards the modelling of systems. The right application of different methodologies together should motivate the development of service-oriented manufacturing systems that embrace the vision of collaborative automation.The authors would like to thank the European Commission and the partners of Network of Excellence “Innovative Production Machines and Systems” (http://www.iproms.org/) and the SOCRADES project (http://www.socrades.eu) for their support.info:eu-repo/semantics/publishedVersio